We report in Table REF , for backbones
formed of a fraction \(f= 40\%\) , \(10\%\)  and \(5\%\)  of the original network, the corresponding number of
temporal edges for each backbone extraction method.
Moreover, Figure REF  in the Supplementary Material shows how
some statistics of the backbones compare to the ones of the original data.
As already discussed in kobayashi2019structural, the ST backbone ties tend to have large weights, with distributions clearly shifted to large values with respect to the original data.
However, while
this happens by definition in the threshold backbone, the distribution of weights in the ST backbone is smooth
and does not have a sharp cutoff at a minimal value.
Moreover, when the group structure is included (GST backbone), the distribution of weights becomes notably broader. This is due to inter-group ties that tend to have lower weights [1]}: these ties appear as significant only when we take into account, through the adequate null model (i.e., through the use of the parameter \(p\) ), that pairs of individuals belonging to different groups have an a priori tendency to form less temporal edges than individuals of the same group. In fact, the ST filter tends to filter out most ties joining nodes of different groups [2]}; the GST filter instead keeps ties both within and between groups.
We also note that both the clustering coefficient
and the modularity of the partition in groups, when
measured in the backbones, can strongly deviate from the values in the original data (see Tables REF 
and REF  in the Supplementary Material).
On the other hand, the
distributions of contact and inter-contact durations are
close to the ones observed in the original data
(see the Supplementary Material).
